Harnessing Big Data in Urban Public Space

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Details

This book advocates new and advanced methods of big data technology so as to analyze the current status of the public space development in China. In the eight chapters of this book, it introduces the theories to develop urban public space, the tools for analytics and evaluation, the cases from China especially Shanghai and global. With analytics and evaluation tools for its scale, space layout, and planning, it aims to improve the quality, efficiency and balanced development of public services such as healthcare and elementary education, serving as the reference and support for decision-making of governments.


Advocates new and advanced methods of big data technology in public space Covers the mechanism for urban public goods supply and innovative model for social governance Explores measures integrating economics and sociology to solve major social challenges in urban-social governance

Autorentext

Wanzhen Chen is an Associate Professor and Master's Supervisor of the School of Social and Public Administration, East China University of Science and Technology. Prolific and proficient in research and teaching in behavioral health and social work, she was awarded the Outstanding PhD Graduate of Zhejiang Province, the Outstanding Achievement Prize of Science Technology of Zhejiang Province, and was selected for the Shanghai Chenguang Talent Plan and the Shanghai Magnolia Talent Plan Pujiang Project. Besides, she has published more than thirty papers, SCI index or SSCI index, and presided over seven national or provincial academic programs, including the program funded by the National Natural Science Foundation of China.


Inhalt

Introduction.- Theoretical Basis and A Review of Research.- Hot Issues and the International Experience in Urban Public Services.- The Layout and Characteristics of Urban Public Service Resources Data Processing and Analysis.- Evaluation for Supply Competence in Urban Public Services.- Evaluation for the Equalization of Public Service Resources.- Factors for Urban Basic Public Services and Case Analysis.- Conclusion and Strategies.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09789819681372
    • Lesemotiv Verstehen
    • Genre Economics
    • Übersetzer Lei Wang
    • Sprache Englisch
    • Anzahl Seiten 196
    • Herausgeber Springer
    • Größe H241mm x B160mm x T17mm
    • Jahr 2025
    • EAN 9789819681372
    • Format Fester Einband
    • ISBN 9819681375
    • Veröffentlichung 01.08.2025
    • Titel Harnessing Big Data in Urban Public Space
    • Autor Wanzhen Chen , Xue Wang
    • Untertitel Analytics and Evaluation
    • Gewicht 463g

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